Jianguo Zhang¹, Biao Hu^2,*, Xiyuan Li¹, Hongxing Zhou², Zhixu Dai³, Yanlei Lu³, Deyang Wang²

Energy Engineering, Vol.118, No.3, pp. 605-614, 2021, DOI:10.32604/EE.2021.014655

Abstract To accurately predict the risk of coal and gas outburst and evaluate the reliability of desorption indexes of drilling cuttings (K₁ and ∆h₂) in No. 16 coal seam of Pingmei No. 12 coal mine, two sets of coal samples were selected from the target coal seams for proximate analyses, methane adsorption/desorption tests, and desorption indexes of drilling cuttings tests. The results indicated that the desorption volume in the initial stage of desorption is large, and increases slowly in the later stage. The methane desorption volume of PMD1 and PMD2 coal samples accounts for 15.14%–18.09% and 15.72%–18.17% respectively in the first… More >

Amal S. Hassan¹, Ehab M. Almetwally^2,*, Gamal M. Ibrahim³

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 337-358, 2021, DOI:10.32604/cmc.2021.013971

Abstract In this paper, an attempt is made to discover the distribution of COVID-19 spread in different countries such as; Saudi Arabia, Italy, Argentina and Angola by specifying an optimal statistical distribution for analyzing the mortality rate of COVID-19. A new generalization of the recently inverted Topp Leone distribution, called Kumaraswamy inverted Topp–Leone distribution, is proposed by combining the Kumaraswamy-G family and the inverted Topp–Leone distribution. We initially provide a linear representation of its density function. We give some of its structure properties, such as quantile function, median, moments, incomplete moments, Lorenz and Bonferroni curves, entropies measures and stress-strength reliability. Then,… More >

Kavita Sahu¹, Fahad A. Alzahrani², R. K. Srivastava¹, Rajeev Kumar^3,4,*

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1471-1488, 2021, DOI:10.32604/cmc.2021.014868

Abstract Maintaining software reliability is the key idea for conducting quality research. This can be done by having less complex applications. While developers and other experts have made significant efforts in this context, the level of reliability is not the same as it should be. Therefore, further research into the most detailed mechanisms for evaluating and increasing software reliability is essential. A significant aspect of growing the degree of reliable applications is the quantitative assessment of reliability. There are multiple statistical as well as soft computing methods available in literature for predicting reliability of software. However, none of these mechanisms are… More >

Feng Zhang^1,*, Yangjun Luo^2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.2, pp. 711-713, 2021, DOI:10.32604/cmes.2021.015567

Abstract This article has no abstract. More >

Yixuan Wang¹, Liping Yuan^2,3, Harish Garg⁴, Ali Bagherinia⁵, Parvïn Hamïd^6,7,8,*, Kim-Hung Pho⁹, Zulkefli Mansor¹⁰

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 369-392, 2021, DOI:10.32604/cmc.2021.012850

Abstract In order to improve performance and robustness of clustering, it is proposed to generate and aggregate a number of primary clusters via clustering ensemble technique. Fuzzy clustering ensemble approaches attempt to improve the performance of fuzzy clustering tasks. However, in these approaches, cluster (or clustering) reliability has not paid much attention to. Ignoring cluster (or clustering) reliability makes these approaches weak in dealing with low-quality base clustering methods. In this paper, we have utilized cluster unreliability estimation and local weighting strategy to propose a new fuzzy clustering ensemble method which has introduced Reliability Based weighted co-association matrix Fuzzy C-Means (RBFCM),… More >

Mohammed Alwabel, Youngmi Kwon^*

Computer Systems Science and Engineering, Vol.36, No.2, pp. 281-292, 2021, DOI:10.32604/csse.2021.014630

Abstract Blockchain is a technology that provides security features that can be used for more than just cryptocurrencies. Blockchain achieves security by saving the information of one block in the next block. Changing the information of one block will require changes to all the next block in order for that change to take effect. Which makes it unfeasible for such an attack to happen. However, the structure of how blockchain works makes the last block always vulnerable for attacks, given that its information is not saved yet in any block. This allows malicious node to change the information of the last… More >

Yang Yang^1,*, Jianxin Wang¹, Zhipeng Gao¹, Yonghua Huo², Xuesong Qiu¹

Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1459-1475, 2020, DOI:10.32604/iasc.2020.011688

Abstract With the vigorous development of the Internet industry and the iterative updating of web service technologies, there are increasing web services with the same or similar functions in the ocean of platforms on the Internet. The issue of selecting the most reliable web service for users has received considerable critical attention. Aiming to solve this task, we propose a service reliability inference method based on deep neural network (SRI-XDFM) in this article. First, according to the pattern of the raw data in our scenario, we improve the performance of embedding by extracting self-correlated information with the help of character encoding… More >

Xiukai Yuan^1,2,*, Jian Gu¹, Shaolong Liu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 331-357, 2021, DOI:10.32604/cmes.2021.010482

Abstract In structural reliability analysis, simulation methods are widely used. The statistical characteristics of failure probability estimate of these methods have been well investigated. In this study, the sensitivities of the failure probability estimate and its statistical characteristics with regard to sample, called ‘contribution indexes’, are proposed to measure the contribution of sample. The contribution indexes in four widely simulation methods, i.e., Monte Carlo simulation (MCS), importance sampling (IS), line sampling (LS) and subset simulation (SS) are derived and analyzed. The proposed contribution indexes of sample can provide valuable information understanding the methods deeply, and enlighten potential improvement of methods. It… More >

Fan Yang^1,2,3,*, Jianwei Ren^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 801-814, 2020, DOI:10.32604/cmes.2020.08889

Abstract Based on the rapid simulation of Markov Chain on samples in failure region, a novel method of reliability analysis combining Monte Carlo Markov Chain (MCMC) with random forest algorithm was proposed. Firstly, a series of samples distributing around limit state function are generated by MCMC. Then, the samples were taken as training data to establish the random forest model. Afterwards, Monte Carlo simulation was used to evaluate the failure probability. Finally, examples demonstrate the proposed method possesses higher computational efficiency and accuracy. More >

Jiaqi He¹, Yangjun Luo^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 777-800, 2020, DOI:10.32604/cmes.2020.010688

Abstract For structures that only the predicted bounds of uncertainties are available, this study proposes a Bayesian method to logically evaluate the nonprobabilistic reliability of structures based on multi-ellipsoid convex model and performance test data. According to the given interval ranges of uncertainties, we determine the initial characteristic parameters of a multi-ellipsoid convex set. Moreover, to update the plausibility of characteristic parameters, a Bayesian network for the information fusion of prior uncertainty knowledge and subsequent performance test data is constructed. Then, an updated multi-ellipsoid set with the maximum likelihood of the performance test data can be achieved. The credible non-probabilistic reliability… More >